{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5d942634",
   "metadata": {},
   "source": [
    "# 上周任务"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "236d6d5f",
   "metadata": {},
   "source": [
    "###  案例名称： 用户画像\n",
    "\n",
    "### 案例描述：\n",
    "#### 导入《用户表》数据，进行如下操作：\n",
    "#### 1.将user_id一列从1开始递增，替换原有一列错误数据，在原数据上进行修改（原数据该列存在重复值）\n",
    "#### 2.将user_name一列中的中文字符提取出来替换原有该列数据\n",
    "#### 3.将chanel_id一列不同渠道占比以饼状图形式进行呈现,并将渠道名称、渠道名称对应的占比情况（保留一位小数即可）也呈现在饼状图上\n",
    "#### 4.绘制柱状图，展现system中不同系统的数量情况，并且在每一个柱子上方标明系统数量值\n",
    "#### 5.根据age年龄一列，绘制年龄分布直方图\n",
    "#### 6.绘制柱状图，展现platform中不同平台的数量情况，并且在每一个柱子上方标明数量值\n",
    "#### 7.手机号段统计\n",
    "#### 中国电信号段：[133,149,153,173,177,180,181,189,191,199]；\n",
    "#### 中国联通号段：[130,131,132,145,155,156,166,171,175,176,185,186]；\n",
    "#### 中国移动号段：[134,135,136,137,138,139,147,150,151,152,157,158,159,172,178,182,183,184,187,188,198]；\n",
    "#### 以上是三大运营商的部分号段，现新增一列运营商类型一列，如果号段在中国电信号段中，则填写中国电信，依次类推，如果数据中存在号段在以上所给号段中均找不到的情况，则填写其他，最后根据运营商类型字段进行分组，绘制柱状图，展现三大运营商占有用户数量情况，并且在每一个柱子上方标明数量值；"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4680016",
   "metadata": {},
   "source": [
    "#### 1.将user_id一列从101开始递增，替换原有一列错误数据，在原数据上进行修改（原数据该列存在重复值）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "df3390e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>user_name</th>\n",
       "      <th>chanel_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>system</th>\n",
       "      <th>IMEI</th>\n",
       "      <th>age</th>\n",
       "      <th>phonenum</th>\n",
       "      <th>platform</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>101</td>\n",
       "      <td>张彬JDZDB7820</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0480</td>\n",
       "      <td>Android</td>\n",
       "      <td>878697695424925</td>\n",
       "      <td>19</td>\n",
       "      <td>187****9863</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>102</td>\n",
       "      <td>朱洁faQL1526</td>\n",
       "      <td>platform_01</td>\n",
       "      <td>city0038</td>\n",
       "      <td>Others</td>\n",
       "      <td>872497106321477</td>\n",
       "      <td>50</td>\n",
       "      <td>189****3565</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>103</td>\n",
       "      <td>那文DcJrkI9253</td>\n",
       "      <td>search_01</td>\n",
       "      <td>city0054</td>\n",
       "      <td>IOS</td>\n",
       "      <td>877746318253724</td>\n",
       "      <td>19</td>\n",
       "      <td>198****4584</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>104</td>\n",
       "      <td>韩金凤TSP3766</td>\n",
       "      <td>search_01</td>\n",
       "      <td>city0466</td>\n",
       "      <td>PC</td>\n",
       "      <td>872746594184694</td>\n",
       "      <td>49</td>\n",
       "      <td>152****9429</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>105</td>\n",
       "      <td>赵伟krfg5598</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0037</td>\n",
       "      <td>PC</td>\n",
       "      <td>872614008637508</td>\n",
       "      <td>30</td>\n",
       "      <td>158****6416</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>264</td>\n",
       "      <td>华佳hXfAab6769</td>\n",
       "      <td>search_02</td>\n",
       "      <td>city0257</td>\n",
       "      <td>IOS</td>\n",
       "      <td>874557516789770</td>\n",
       "      <td>18</td>\n",
       "      <td>133****0176</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>265</td>\n",
       "      <td>胡雪梅As7856</td>\n",
       "      <td>platform_01</td>\n",
       "      <td>city0075</td>\n",
       "      <td>PC</td>\n",
       "      <td>873411295606408</td>\n",
       "      <td>36</td>\n",
       "      <td>157****5988</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>266</td>\n",
       "      <td>易婷婷wDjnc9029</td>\n",
       "      <td>guide_03</td>\n",
       "      <td>city0029</td>\n",
       "      <td>PC</td>\n",
       "      <td>870640569926414</td>\n",
       "      <td>50</td>\n",
       "      <td>196****5966</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>267</td>\n",
       "      <td>徐帆Ykoez4438</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0388</td>\n",
       "      <td>IOS</td>\n",
       "      <td>872952049638870</td>\n",
       "      <td>45</td>\n",
       "      <td>190****4764</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>268</td>\n",
       "      <td>乔鹏FaSEz765</td>\n",
       "      <td>search_03</td>\n",
       "      <td>city0073</td>\n",
       "      <td>PC</td>\n",
       "      <td>874246261491881</td>\n",
       "      <td>42</td>\n",
       "      <td>158****8922</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>168 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     user_id     user_name    chanel_id   city_id   system             IMEI  \\\n",
       "0        101   张彬JDZDB7820     guide_02  city0480  Android  878697695424925   \n",
       "1        102    朱洁faQL1526  platform_01  city0038   Others  872497106321477   \n",
       "2        103  那文DcJrkI9253    search_01  city0054      IOS  877746318253724   \n",
       "3        104    韩金凤TSP3766    search_01  city0466       PC  872746594184694   \n",
       "4        105    赵伟krfg5598     guide_02  city0037       PC  872614008637508   \n",
       "..       ...           ...          ...       ...      ...              ...   \n",
       "163      264  华佳hXfAab6769    search_02  city0257      IOS  874557516789770   \n",
       "164      265     胡雪梅As7856  platform_01  city0075       PC  873411295606408   \n",
       "165      266  易婷婷wDjnc9029     guide_03  city0029       PC  870640569926414   \n",
       "166      267   徐帆Ykoez4438     guide_02  city0388      IOS  872952049638870   \n",
       "167      268    乔鹏FaSEz765    search_03  city0073       PC  874246261491881   \n",
       "\n",
       "     age     phonenum platform  \n",
       "0     19  187****9863      APP  \n",
       "1     50  189****3565      APP  \n",
       "2     19  198****4584      APP  \n",
       "3     49  152****9429       PC  \n",
       "4     30  158****6416       PC  \n",
       "..   ...          ...      ...  \n",
       "163   18  133****0176      APP  \n",
       "164   36  157****5988       PC  \n",
       "165   50  196****5966       PC  \n",
       "166   45  190****4764      APP  \n",
       "167   42  158****8922       PC  \n",
       "\n",
       "[168 rows x 9 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 导包\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt  \n",
    "import pandas as pd\n",
    "# 设置字体格式\n",
    "plt.rcParams['font.family'] = ['sans-serif']\n",
    "plt.rcParams['font.sans-serif'] = 'Arial Unicode MS'\n",
    "\n",
    "data = pd.read_excel('用户表.xlsx')\n",
    "data['user_id'] = [i for i in range(101,data.shape[0]+101)]\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23a71936",
   "metadata": {},
   "source": [
    "#### 2.将user_name一列中的中文字符提取出来替换原有该列数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "2fbf4296",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>user_name</th>\n",
       "      <th>chanel_id</th>\n",
       "      <th>city_id</th>\n",
       "      <th>system</th>\n",
       "      <th>IMEI</th>\n",
       "      <th>age</th>\n",
       "      <th>phonenum</th>\n",
       "      <th>platform</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>101</td>\n",
       "      <td>张彬</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0480</td>\n",
       "      <td>Android</td>\n",
       "      <td>878697695424925</td>\n",
       "      <td>19</td>\n",
       "      <td>187****9863</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>102</td>\n",
       "      <td>朱洁</td>\n",
       "      <td>platform_01</td>\n",
       "      <td>city0038</td>\n",
       "      <td>Others</td>\n",
       "      <td>872497106321477</td>\n",
       "      <td>50</td>\n",
       "      <td>189****3565</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>103</td>\n",
       "      <td>那文</td>\n",
       "      <td>search_01</td>\n",
       "      <td>city0054</td>\n",
       "      <td>IOS</td>\n",
       "      <td>877746318253724</td>\n",
       "      <td>19</td>\n",
       "      <td>198****4584</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>104</td>\n",
       "      <td>韩金凤</td>\n",
       "      <td>search_01</td>\n",
       "      <td>city0466</td>\n",
       "      <td>PC</td>\n",
       "      <td>872746594184694</td>\n",
       "      <td>49</td>\n",
       "      <td>152****9429</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>105</td>\n",
       "      <td>赵伟</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0037</td>\n",
       "      <td>PC</td>\n",
       "      <td>872614008637508</td>\n",
       "      <td>30</td>\n",
       "      <td>158****6416</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>264</td>\n",
       "      <td>华佳</td>\n",
       "      <td>search_02</td>\n",
       "      <td>city0257</td>\n",
       "      <td>IOS</td>\n",
       "      <td>874557516789770</td>\n",
       "      <td>18</td>\n",
       "      <td>133****0176</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>265</td>\n",
       "      <td>胡雪梅</td>\n",
       "      <td>platform_01</td>\n",
       "      <td>city0075</td>\n",
       "      <td>PC</td>\n",
       "      <td>873411295606408</td>\n",
       "      <td>36</td>\n",
       "      <td>157****5988</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>266</td>\n",
       "      <td>易婷婷</td>\n",
       "      <td>guide_03</td>\n",
       "      <td>city0029</td>\n",
       "      <td>PC</td>\n",
       "      <td>870640569926414</td>\n",
       "      <td>50</td>\n",
       "      <td>196****5966</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>267</td>\n",
       "      <td>徐帆</td>\n",
       "      <td>guide_02</td>\n",
       "      <td>city0388</td>\n",
       "      <td>IOS</td>\n",
       "      <td>872952049638870</td>\n",
       "      <td>45</td>\n",
       "      <td>190****4764</td>\n",
       "      <td>APP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>268</td>\n",
       "      <td>乔鹏</td>\n",
       "      <td>search_03</td>\n",
       "      <td>city0073</td>\n",
       "      <td>PC</td>\n",
       "      <td>874246261491881</td>\n",
       "      <td>42</td>\n",
       "      <td>158****8922</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>168 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     user_id user_name    chanel_id   city_id   system             IMEI  age  \\\n",
       "0        101        张彬     guide_02  city0480  Android  878697695424925   19   \n",
       "1        102        朱洁  platform_01  city0038   Others  872497106321477   50   \n",
       "2        103        那文    search_01  city0054      IOS  877746318253724   19   \n",
       "3        104       韩金凤    search_01  city0466       PC  872746594184694   49   \n",
       "4        105        赵伟     guide_02  city0037       PC  872614008637508   30   \n",
       "..       ...       ...          ...       ...      ...              ...  ...   \n",
       "163      264        华佳    search_02  city0257      IOS  874557516789770   18   \n",
       "164      265       胡雪梅  platform_01  city0075       PC  873411295606408   36   \n",
       "165      266       易婷婷     guide_03  city0029       PC  870640569926414   50   \n",
       "166      267        徐帆     guide_02  city0388      IOS  872952049638870   45   \n",
       "167      268        乔鹏    search_03  city0073       PC  874246261491881   42   \n",
       "\n",
       "        phonenum platform  \n",
       "0    187****9863      APP  \n",
       "1    189****3565      APP  \n",
       "2    198****4584      APP  \n",
       "3    152****9429       PC  \n",
       "4    158****6416       PC  \n",
       "..           ...      ...  \n",
       "163  133****0176      APP  \n",
       "164  157****5988       PC  \n",
       "165  196****5966       PC  \n",
       "166  190****4764      APP  \n",
       "167  158****8922       PC  \n",
       "\n",
       "[168 rows x 9 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re \n",
    "# data.user_name = data.user_name.apply(lambda x: ''.join(re.findall(r'[\\u4E00-\\u9FEF]',x)))\n",
    "# data \n",
    "\n",
    "# data.user_name.apply(lambda x :) \n",
    "\n",
    "# \\u Unicode 编码的标志\n",
    "# \\u4E00-\\u9FEF 中文字符 \n",
    "def func_apply(x) :\n",
    "   \n",
    "    return ''.join(re.findall(r'[\\u4E00-\\u9FEF]',x))\n",
    "# 1. apply \n",
    "# 2. re \n",
    "data.user_name = data.user_name.apply(func_apply)\n",
    "data\n",
    "\n",
    "data.user_name = data.user_name.apply(lambda x: ''.join(re.findall(r'[\\u4E00-\\u9FEF]',x))) \n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a233b74",
   "metadata": {},
   "source": [
    "#### 3.将chanel_id一列不同渠道占比以饼状图形式进行呈现,并将渠道名称、渠道名称对应的占比情况（保留一位小数即可）也呈现在饼状图上"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "90fad2a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.series.Series'>\n",
      "Index(['union_01', 'platform_01', 'search_01', 'platform_02', 'guide_01',\n",
      "       'union_02', 'guide_02', 'guide_03', 'union_03', 'search_03',\n",
      "       'platform_03', 'search_02'],\n",
      "      dtype='object')\n",
      "[21 19 19 18 17 15 13 11 11 10  8  6]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.chanel_id.value_counts() \n",
    "print(type(data.chanel_id.value_counts() ))\n",
    "print(data.chanel_id.value_counts().index)\n",
    "print(data.chanel_id.value_counts().values)\n",
    "plt.figure(figsize=(10,6),dpi=100)\n",
    "patches, l_text, p_text = plt.pie(data.chanel_id.value_counts(),\n",
    "                                 labels=data.chanel_id.value_counts().index ,\n",
    "                                 labeldistance= 1.1, \n",
    "                                 autopct= \"%1.1f%%\",\n",
    "                                 shadow=False,\n",
    "                                 startangle= 90, \n",
    "                                 pctdistance = 0.6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fee79cf",
   "metadata": {},
   "source": [
    "#### 4.绘制柱状图，展现system中不同系统的数量情况，并且在每一个柱子上方标明系统数量值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "14b70b3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.system.value_counts().index \n",
    "data.system.value_counts().values\n",
    "plt.figure(figsize=(6,4),dpi=100) \n",
    "bars = plt.bar(x= data.system.value_counts().index , height=data.system.value_counts().values) \n",
    "for i in bars :\n",
    "    height = i.get_height() \n",
    "    plt.text(i.get_x()+i.get_width()/2, height+0.5,str(int(height)),ha='center')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fec122e2",
   "metadata": {},
   "source": [
    "#### 5.根据age年龄一列，绘制年龄分布直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "19f0a47c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,4),dpi=100) \n",
    "bars = plt.hist(data.age,bins=30) \n",
    "plt.xticks(range(data.age.min(),data.age.max()+2,2))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5d9bf5e",
   "metadata": {},
   "source": [
    "#### 6.绘制柱状图，展现platform中不同平台的数量情况，并且在每一个柱子上方标明数量值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "568b1058",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kSWpYr07ui4idgRnAh4AvUUV7bZfV1gIjtrKZa4BVdZclvZlFkiT1XMPhj4jdgV8AHwWOycw/AKuB4V1WHV5b3p3rqc4H6Lzs0+gskiSpMY2e1T8ZeBpYCfxJZv62dtVCqsP99SYDz3W3rczcmJntnRe2/iRBkiQ1QSNn9e8NzKI6ae/0Wqw7/QTYIyIuiYghEXEccAYws6nTSpKk7dLIHv8lwG7AfwJWR8Sa2mVhZq4ApgAXUL22PxO4NDNnN3tgSZLUe0N7umJmfonqRL7urp8DHNaMoSRJUt/wLXslSSqI4ZckqSCGX5Kkghh+SZIKYvglSSqI4Zck7XDLly/n/e9/P7Nnz3572fTp0znggAMYNWoUhxxyCA888EDrBhzEDL8kaYeaM2cOH/3oR3nxxRffXvbQQw/xxS9+kXvvvZf29nZmzpzJWWedxfPPP9/CSQcnwy9J2mHuuusuzjzzTK6//vrNlp988sm8+OKLHHHEEWzatIkVK1awfv16Fi1a1KJJB68ev4GPJEnb68QTT+Tss89m6NDN8zNkyBDGjBnDCy+8wMSJE+no6OAjH/kIn/zkJ1s06eDlHr8kaYfZc8893xH9evvvvz/r16/nqaee4gMf+ADLli3bgdOVwfBLkvqNoUOHMnToUA477DAmTZrEZZdd1uqRBh3DL0lquWnTpvHpT396s2Xr169nyZIlLZpo8DL8kqSWO+aYY7j//vu5//772bRpE4899hg333zzO54MaPt5cp8kqeWOOOIIfvSjH3HddddxzjnnsPfee3Pttddy+eWXt3q0QcfwS5JaIjM3+/zUU0/l1FNPbdE05TD8ktTPjL/64VaPoD62+IYpLbttX+OXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpIIYfkmSCmL4JUkqiOGXJKkghl+SpII0NfwRsUdE/CQiVkfE8oi4JSJ2buZtSJKk3mv2Hv99QAewN3AIcBxwXZNvQ5Ik9VLTwh8R+wMfB67MzNWZ+QpwA3Bus25DkiRtn6FN3NYk4LXMXFK3bD7wnogYk5mv168cEcOAYXWLRgK0t7c3cSTYtHFdU7en/qfZ95me8r41+HnfUl9p9n2rke1FZjblRiPiHODvMnPfumX7A78B3tvlCQER8RXgy025cUmSBLBP7Yh7t5q5x78aGN5l2fC667q6HpjWZdm7gdeaOFOJRgJLgH3Y8r+71Fvet9RXvG81x0jg99taqZnhXwi8OyLeU/dsYzKwJDNXdV05MzcCG7ssbs1xtUEkIjo/XJ2Z/nuqabxvqa9432qaHv3bNe3kvsz8NfAYcENE7BoR7wO+BMxo1m1IkqTt0+wf5/s0MAZYCjwJ/Bz4uybfhiRJ6qVmHuonM38PnNLMbaphG4Gv8s6XUaTt5X1LfcX71g7UtLP6JUlS/+d79UuSVBDDL0lSQQy/JEkFMfySJBXE8A8gEXFRRGyKiKldlt8VEW9GxJq6y/KI+GFEjK+tc2xEZJd1VkfE3Ij4y1b8fdS/RMTiiNhQd99YExG/i4hpEbFrbZ1dI+K6iFgUEWsjYmlE/CwiDmv1/Nq22mNARsQHtnDdlbXrvlL7/O8j4u97uN2FEXFW7eNtPh6ptQz/wPKfgVuByyOi649i3pOZIzovwARgT+De+pW6rDOG6lcp3xsRH9oB86v/u7h2/xhZu4+cBJwFXBcRbcBsYArwGWAs8AHgWeBXEXFEi2ZWY5ZT/f91dS51b5memRdn5sU92WBmHpyZ99Qt6tHjkVrD8A8QEXEssBdwdW3Rn29t/cx8DfhHYOJW1nmL6p0VhwAHNWVQDSqZuQj4FdX96Aqq0J+UmfMy843MbM/M64DbqX5Dp/q/e4C/jrr3yY2II4EEFtQtuysi7qp9/JWI+FFE/ENEvB4RL0fE1XXrLo6Iz3Z3g10fj2rb+3lE/Gtte/8+IsZExPSIWFI7QvBgREyou43Dakco10TE0xFxVUQsrl332Yh4MiJ+GhGrIuKvImK3iLg7Iv5Y+5rfRMS5ddvLiLgiIn4bEesi4oHabfxb7YjXvC0dGRkMDP/AcSnw3zNzPdVe/+e7WzEihkTEQcB5wC+2st5Y4FqqX4rxeHPH1UAXETtHxCeAE6juR38G/Lz2IL6ZzLwyM7+3o2dUrzwM7Ap8vG7ZecCd2/i604F/BvagOmJwfUT8ybZubCuPRycC/43qF/M8DvwPqieWhwP7Uv1m1/8VEaNrR5serN3+OOCzVI+J9Q6nenKxB/AzYCbwBvA+YBQwHbi982Wrmr8Ajqyt8zHgAeCC2m2sr8036Bj+ASAi3kv1TXJbbdEM4IMR8ad1q51Ze+b8OrCS6ptkLtU3W/22Xq9b73ngUODE2rsuStPr7h/LgG9R/brtW4Hd6cFv/lK/9ybVXv9noTpvAzgNuHsbX7cwM39QO9LzS6q3Zp/Qzbo9eTxalJmPZeYaYDeqd329IjNfzcx1wH8BdgZOBv4jEMBXM3NjZs4HvtHlNlcD99auXwf8DdVRqjeB/WrX71y7rU7fyczlmfkqsAj4cWYuysw3gH8Fxm/j32RAaupb9qrPXAK0AX+sOzoH1TfGo7WPf5CZn93WhjJzTNOn02BySWbe1c11f6DaO3uHiBgDrKs9YKr/+x7wbxFxCfAp4NHMXN7l8aWrrkd61gM7dbNuTx6Pltd9vG/tz992LsjMtyLiJar4vgW8lJmb6r7mN13ny83fivb9wNeonpwsBl6oLa+f+dW6j9+iepLSqYNBunM8KP9Sg0lE7EJ16OmkzIzOC3AIMCUiDmzthCrIg8Anay8RdXUX8NMdO456q7bH/H+pzhU6l20f5u9rv6v9uX/ngtoJzOOpjjK9BOwbmz8z2a+7jUXEMOAh4B+AvTLzKOC7W1h10xaWDXqGv//7K6pnov9Sv7D2jfsUcGUrhlKRbqN6EH6wdhLUThHx7oi4Hjge+HJrx1ODvgdMpXpdvdtzgXaE2qH2h4BbImLP2ssPf0u1d/5g7ZLAtRHxrtpPIV21lU0OBXYBNmVmRsT+/P+XBnbuq7/HQGH4+7+/oTps9tYWrvsucA7VySxSn6q9bvqnwDyqk6jagf8DHAgck5lPtnA8Ne4HVP933+/m8WVHO4fqvKOngCXAh4CjM/O1zFxLdZLpx6kOz98N/E+qk/feobb+ecCXI2IN1d/1b6lerjq0j/8e/Z6/nU+S1K9FxLuBD2XmnLplnwc+lZlHt26ygck9fklSf7cT8L8jYgpAROxHtUf/UEunGqDc45ck9XsRcTrwVaqT+l6n+rn/r2Tmmy0dbAAy/JIkFcRD/ZIkFcTwS5JUEMMvSVJBDL8kSQUx/JIkFcTwS5JUEMMvSVJBDL8kSQX5f4UROUH5NLoNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(6,4),dpi=100) \n",
    "bars = plt.bar(x= data.platform.value_counts().index , height=data.platform.value_counts().values) \n",
    "for i in bars :\n",
    "    height = i.get_height() \n",
    "    plt.text(i.get_x()+i.get_width()/2, height+0.5,str(int(height)),ha='center')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24fd099a",
   "metadata": {},
   "source": [
    "#### 7.手机号段统计\n",
    "#### 中国电信号段：[133,149,153,173,177,180,181,189,191,199]；\n",
    "#### 中国联通号段：[130,131,132,145,155,156,166,171,175,176,185,186]；\n",
    "#### 中国移动号段：[134,135,136,137,138,139,147,150,151,152,157,158,159,172,178,182,183,184,187,188,198]；\n",
    "#### 以上是三大运营商的部分号段，现新增一列运营商类型一列，如果号段在中国电信号段中，则填写中国电信，依次类推，如果数据中存在号段在以上所给号段中均找不到的情况，则填写其他，最后根据运营商类型字段进行分组，绘制柱状图，展现三大运营商占有用户数量情况，并且在每一个柱子上方标明数量值；"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "8eabe2d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def phonenum_in(d):\n",
    "    if d in [133,149,153,173,177,180,181,189,191,199]:\n",
    "        return '中国电信'\n",
    "    elif d in [130,131,132,145,155,156,166,171,175,176,185,186]:\n",
    "        return '中国联通' \n",
    "    elif d in [134,135,136,137,138,139,147,150,151,152,157,158,159,172,178,182,183,184,187,188,198] :\n",
    "        return '中国移动' \n",
    "    else: \n",
    "        return '其他'\n",
    "data['type'] = data.phonenum.str[0:3].astype('int').apply(phonenum_in)\n",
    "data \n",
    "\n",
    "plt.figure(figsize=(6,4),dpi=100) \n",
    "bars = plt.bar(x= data.type.value_counts().index , height=data.type.value_counts().values) \n",
    "for i in bars :\n",
    "    height = i.get_height() \n",
    "    plt.text(i.get_x()+i.get_width()/2, height+0.5,str(int(height)),ha='center')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d634fa6",
   "metadata": {},
   "source": [
    "# 昨日任务 "
   ]
  },
  {
   "attachments": {
    "%E7%81%AB%E5%BD%B1ab%E8%A1%A8.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "df5728e1",
   "metadata": {},
   "source": [
    "###  案例名称： 火影忍者分析\n",
    "\n",
    "### 案例描述：\n",
    "#### 现有两个表格:将表格a、表格b以Excel形式进行存储，即：保存到Excel文件中\n",
    "![%E7%81%AB%E5%BD%B1ab%E8%A1%A8.png](attachment:%E7%81%AB%E5%BD%B1ab%E8%A1%A8.png)\n",
    "#### 现需求如下:\n",
    "#### 1.\t将a表、b表导入，以dataframe形式进行存储\n",
    "#### 2.\t将b表中的地区一列添加到a表中\n",
    "#### 3.\t补全a表星座一列数据，比如：天秤，改成天秤座，正常的数据不用修改\n",
    "#### 4.\t取出a表中出生日期在2010年7月之前的数据\n",
    "#### 5.\t计算不同星座的人数数量\n",
    "#### 6.\t计算不同血型不同星座的能量平均值\n",
    "#### 7.\t假设能量值在【100,400】之间称之为下忍，【401,600】之间称之为中忍，【601,800】之间称之为上忍，【801,1000】之间称之为火影，请在a表最后增加一列：忍者类型\n",
    "#### 8.\t计算每一年出生的人数\n",
    "#### 9.\t取出a表名称中含有宇智波的数据\n",
    "#### 10.\t找出b表名称不在a表中的名称\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a14a951",
   "metadata": {},
   "source": [
    "#### 1.\t将a表、b表导入，以dataframe形式进行存储"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "f2a19936",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>地区</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>漩涡鸣人</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>旗木卡卡西</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>日向雏田</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>我爱罗</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>勘九郎</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>鬼灯水月</td>\n",
       "      <td>血雾村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>宇智波带土</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>四代风影</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>桃地再不斩</td>\n",
       "      <td>雾隐村</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       名称   地区\n",
       "0    漩涡鸣人  木叶村\n",
       "1   宇智波佐助  木叶村\n",
       "2   旗木卡卡西  木叶村\n",
       "3    宇智波斑  木叶村\n",
       "4    宇智波鼬  木叶村\n",
       "5    日向雏田  木叶村\n",
       "6     我爱罗  砂隐村\n",
       "7     勘九郎  砂隐村\n",
       "8    鬼灯水月  血雾村\n",
       "9   宇智波带土  木叶村\n",
       "10   四代风影  砂隐村\n",
       "11  桃地再不斩  雾隐村"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 导包\n",
    "import numpy as np \n",
    "import matplotlib.pyplot as plt  \n",
    "import pandas as pd\n",
    "# 设置字体格式\n",
    "plt.rcParams['font.family'] = ['sans-serif']\n",
    "plt.rcParams['font.sans-serif'] = 'Arial Unicode MS' \n",
    "\n",
    "a = pd.read_excel('火影a表.xlsx') \n",
    "a\n",
    "b = pd.read_excel('火影b表.xlsx') \n",
    "b "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1097fa57",
   "metadata": {},
   "source": [
    "#### 2.\t将b表中的地区一列添加到a表中"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "7884b48e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>血型</th>\n",
       "      <th>性别</th>\n",
       "      <th>星座</th>\n",
       "      <th>出生日期</th>\n",
       "      <th>能量值</th>\n",
       "      <th>地区</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>漩涡鸣人</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>天秤</td>\n",
       "      <td>2012-04-15</td>\n",
       "      <td>987</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>狮子</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>900</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>旗木卡卡西</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>处女座</td>\n",
       "      <td>2001-02-17</td>\n",
       "      <td>680</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯</td>\n",
       "      <td>2090-06-18</td>\n",
       "      <td>813</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>双子座</td>\n",
       "      <td>2002-07-28</td>\n",
       "      <td>790</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>日向雏田</td>\n",
       "      <td>A</td>\n",
       "      <td>女</td>\n",
       "      <td>摩羯</td>\n",
       "      <td>2010-08-11</td>\n",
       "      <td>665</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>我爱罗</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>630</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>勘九郎</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>金牛</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>343</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>鬼灯水月</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>水瓶座</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>468</td>\n",
       "      <td>血雾村</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区\n",
       "0   漩涡鸣人   B  男   天秤 2012-04-15  987  木叶村\n",
       "1  宇智波佐助  AB  男   狮子 2012-04-23  900  木叶村\n",
       "2  旗木卡卡西   O  男  处女座 2001-02-17  680  木叶村\n",
       "3   宇智波斑   O  男   摩羯 2090-06-18  813  木叶村\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村\n",
       "5   日向雏田   A  女   摩羯 2010-08-11  665  木叶村\n",
       "6    我爱罗  AB  男  摩羯座 2020-12-21  630  砂隐村\n",
       "7    勘九郎   B  男   金牛 2017-03-27  343  砂隐村\n",
       "8   鬼灯水月   B  男  水瓶座 2021-01-07  468  血雾村"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a =  pd.merge(a,b,on='名称',how='left')\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8bba9bc",
   "metadata": {},
   "source": [
    "#### 3.\t补全a表星座一列数据，比如：天秤，改成天秤座，正常的数据不用修改"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "80b9171f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>血型</th>\n",
       "      <th>性别</th>\n",
       "      <th>星座</th>\n",
       "      <th>出生日期</th>\n",
       "      <th>能量值</th>\n",
       "      <th>地区</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>天秤座</td>\n",
       "      <td>2012-04-15</td>\n",
       "      <td>987</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>狮子座</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>900</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>旗木卡卡西</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>处女座</td>\n",
       "      <td>2001-02-17</td>\n",
       "      <td>680</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2090-06-18</td>\n",
       "      <td>813</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>双子座</td>\n",
       "      <td>2002-07-28</td>\n",
       "      <td>790</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>日向雏田</td>\n",
       "      <td>A</td>\n",
       "      <td>女</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2010-08-11</td>\n",
       "      <td>665</td>\n",
       "      <td>木叶村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>我爱罗</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>630</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>勘九郎</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>金牛座</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>343</td>\n",
       "      <td>砂隐村</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>鬼灯水月</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>水瓶座</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>468</td>\n",
       "      <td>血雾村</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区\n",
       "0   漩涡鸣人   B  男  天秤座 2012-04-15  987  木叶村\n",
       "1  宇智波佐助  AB  男  狮子座 2012-04-23  900  木叶村\n",
       "2  旗木卡卡西   O  男  处女座 2001-02-17  680  木叶村\n",
       "3   宇智波斑   O  男  摩羯座 2090-06-18  813  木叶村\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村\n",
       "5   日向雏田   A  女  摩羯座 2010-08-11  665  木叶村\n",
       "6    我爱罗  AB  男  摩羯座 2020-12-21  630  砂隐村\n",
       "7    勘九郎   B  男  金牛座 2017-03-27  343  砂隐村\n",
       "8   鬼灯水月   B  男  水瓶座 2021-01-07  468  血雾村"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.星座 = a.星座.apply(lambda x: x+'座' if len(x)!=3 else x)\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "062c0b40",
   "metadata": {},
   "source": [
    "#### 4.\t取出a表中出生日期在2010年7月之前的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "9be5f4e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>AB</td>\n",
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      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区\n",
       "2  旗木卡卡西   O  男  处女座 2001-02-17  680  木叶村\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村"
      ]
     },
     "execution_count": 124,
     "metadata": {},
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    }
   ],
   "source": [
    "a[a.出生日期<'2010-07']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6269e6f",
   "metadata": {},
   "source": [
    "#### 5.\t计算不同星座的人数数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "246ea257",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "摩羯座    3\n",
       "处女座    1\n",
       "水瓶座    1\n",
       "金牛座    1\n",
       "双子座    1\n",
       "狮子座    1\n",
       "天秤座    1\n",
       "Name: 星座, dtype: int64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.星座.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52d92f56",
   "metadata": {},
   "source": [
    "#### 6.\t计算不同血型不同星座的能量平均值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "7d8f50dc",
   "metadata": {},
   "outputs": [
    {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>能量值</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>血型</th>\n",
       "      <th>星座</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>摩羯座</th>\n",
       "      <td>665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">AB</th>\n",
       "      <th>双子座</th>\n",
       "      <td>790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>摩羯座</th>\n",
       "      <td>630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>狮子座</th>\n",
       "      <td>900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">B</th>\n",
       "      <th>天秤座</th>\n",
       "      <td>987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>水瓶座</th>\n",
       "      <td>468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金牛座</th>\n",
       "      <td>343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">O</th>\n",
       "      <th>处女座</th>\n",
       "      <td>680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>摩羯座</th>\n",
       "      <td>813</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        能量值\n",
       "血型 星座      \n",
       "A  摩羯座  665\n",
       "AB 双子座  790\n",
       "   摩羯座  630\n",
       "   狮子座  900\n",
       "B  天秤座  987\n",
       "   水瓶座  468\n",
       "   金牛座  343\n",
       "O  处女座  680\n",
       "   摩羯座  813"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.groupby(by=['血型','星座']).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "506f6c41",
   "metadata": {},
   "source": [
    "#### 7.\t假设能量值在【100,400】之间称之为下忍，【401,600】之间称之为中忍，【601,800】之间称之为上忍，【801,1000】之间称之为火影，请在a表最后增加一列：忍者类型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "5875a475",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>血型</th>\n",
       "      <th>性别</th>\n",
       "      <th>星座</th>\n",
       "      <th>出生日期</th>\n",
       "      <th>能量值</th>\n",
       "      <th>地区</th>\n",
       "      <th>忍者类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>漩涡鸣人</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>天秤座</td>\n",
       "      <td>2012-04-15</td>\n",
       "      <td>987</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>狮子座</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>900</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>旗木卡卡西</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>处女座</td>\n",
       "      <td>2001-02-17</td>\n",
       "      <td>680</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2090-06-18</td>\n",
       "      <td>813</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>双子座</td>\n",
       "      <td>2002-07-28</td>\n",
       "      <td>790</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>日向雏田</td>\n",
       "      <td>A</td>\n",
       "      <td>女</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2010-08-11</td>\n",
       "      <td>665</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>我爱罗</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>630</td>\n",
       "      <td>砂隐村</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>勘九郎</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>金牛座</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>343</td>\n",
       "      <td>砂隐村</td>\n",
       "      <td>下忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>鬼灯水月</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>水瓶座</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>468</td>\n",
       "      <td>血雾村</td>\n",
       "      <td>中忍</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区 忍者类型\n",
       "0   漩涡鸣人   B  男  天秤座 2012-04-15  987  木叶村   火影\n",
       "1  宇智波佐助  AB  男  狮子座 2012-04-23  900  木叶村   火影\n",
       "2  旗木卡卡西   O  男  处女座 2001-02-17  680  木叶村   上忍\n",
       "3   宇智波斑   O  男  摩羯座 2090-06-18  813  木叶村   火影\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村   上忍\n",
       "5   日向雏田   A  女  摩羯座 2010-08-11  665  木叶村   上忍\n",
       "6    我爱罗  AB  男  摩羯座 2020-12-21  630  砂隐村   上忍\n",
       "7    勘九郎   B  男  金牛座 2017-03-27  343  砂隐村   下忍\n",
       "8   鬼灯水月   B  男  水瓶座 2021-01-07  468  血雾村   中忍"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def judge(x):\n",
    "    if x>=100 and x<=400:\n",
    "        return '下忍'\n",
    "    elif x>=401 and x<=600:\n",
    "        return '中忍'\n",
    "    elif x>=601 and x<=800:\n",
    "        return '上忍'\n",
    "    else:\n",
    "        return '火影'\n",
    "a['忍者类型'] = a.能量值.apply(judge)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "33c94ab5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>名称</th>\n",
       "      <th>血型</th>\n",
       "      <th>性别</th>\n",
       "      <th>星座</th>\n",
       "      <th>出生日期</th>\n",
       "      <th>能量值</th>\n",
       "      <th>地区</th>\n",
       "      <th>忍者类型</th>\n",
       "      <th>忍者类型忍者类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>漩涡鸣人</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>天秤座</td>\n",
       "      <td>2012-04-15</td>\n",
       "      <td>987</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>狮子座</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>900</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>旗木卡卡西</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>处女座</td>\n",
       "      <td>2001-02-17</td>\n",
       "      <td>680</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2090-06-18</td>\n",
       "      <td>813</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>双子座</td>\n",
       "      <td>2002-07-28</td>\n",
       "      <td>790</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>日向雏田</td>\n",
       "      <td>A</td>\n",
       "      <td>女</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2010-08-11</td>\n",
       "      <td>665</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>我爱罗</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2020-12-21</td>\n",
       "      <td>630</td>\n",
       "      <td>砂隐村</td>\n",
       "      <td>上忍</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>勘九郎</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>金牛座</td>\n",
       "      <td>2017-03-27</td>\n",
       "      <td>343</td>\n",
       "      <td>砂隐村</td>\n",
       "      <td>下忍</td>\n",
       "      <td>下忍</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>鬼灯水月</td>\n",
       "      <td>B</td>\n",
       "      <td>男</td>\n",
       "      <td>水瓶座</td>\n",
       "      <td>2021-01-07</td>\n",
       "      <td>468</td>\n",
       "      <td>血雾村</td>\n",
       "      <td>中忍</td>\n",
       "      <td>中忍</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区 忍者类型 忍者类型忍者类型\n",
       "0   漩涡鸣人   B  男  天秤座 2012-04-15  987  木叶村   火影       火影\n",
       "1  宇智波佐助  AB  男  狮子座 2012-04-23  900  木叶村   火影       火影\n",
       "2  旗木卡卡西   O  男  处女座 2001-02-17  680  木叶村   上忍       上忍\n",
       "3   宇智波斑   O  男  摩羯座 2090-06-18  813  木叶村   火影       火影\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村   上忍       上忍\n",
       "5   日向雏田   A  女  摩羯座 2010-08-11  665  木叶村   上忍       上忍\n",
       "6    我爱罗  AB  男  摩羯座 2020-12-21  630  砂隐村   上忍       上忍\n",
       "7    勘九郎   B  男  金牛座 2017-03-27  343  砂隐村   下忍       下忍\n",
       "8   鬼灯水月   B  男  水瓶座 2021-01-07  468  血雾村   中忍       中忍"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cut（data, \n",
    "#        bins, (99,400] , (400,600] , (600,800] , (800,1000] , \n",
    "#      labels)\n",
    "\n",
    "a['忍者类型忍者类型'] = pd.cut(a['能量值'],\n",
    "      bins=[99,400,600,800,1000],\n",
    "      labels=['下忍','中忍','上忍','火影']) \n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f313590",
   "metadata": {},
   "source": [
    "#### 8.\t计算每一年出生的人数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "beb90cd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "出生日期\n",
       "2001    1\n",
       "2002    1\n",
       "2010    1\n",
       "2012    2\n",
       "2017    1\n",
       "2020    1\n",
       "2021    1\n",
       "2090    1\n",
       "Name: 名称, dtype: int64"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.groupby(by=a.出生日期.dt.year)['名称'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94f374c9",
   "metadata": {},
   "source": [
    "#### 9.\t取出a表名称中含有宇智波的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "36846248",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>血型</th>\n",
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       "      <th>忍者类型忍者类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>宇智波佐助</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>狮子座</td>\n",
       "      <td>2012-04-23</td>\n",
       "      <td>900</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>宇智波斑</td>\n",
       "      <td>O</td>\n",
       "      <td>男</td>\n",
       "      <td>摩羯座</td>\n",
       "      <td>2090-06-18</td>\n",
       "      <td>813</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>火影</td>\n",
       "      <td>火影</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>宇智波鼬</td>\n",
       "      <td>AB</td>\n",
       "      <td>男</td>\n",
       "      <td>双子座</td>\n",
       "      <td>2002-07-28</td>\n",
       "      <td>790</td>\n",
       "      <td>木叶村</td>\n",
       "      <td>上忍</td>\n",
       "      <td>上忍</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      名称  血型 性别   星座       出生日期  能量值   地区 忍者类型 忍者类型忍者类型\n",
       "1  宇智波佐助  AB  男  狮子座 2012-04-23  900  木叶村   火影       火影\n",
       "3   宇智波斑   O  男  摩羯座 2090-06-18  813  木叶村   火影       火影\n",
       "4   宇智波鼬  AB  男  双子座 2002-07-28  790  木叶村   上忍       上忍"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[a.名称.apply(lambda x : True if '宇智波' in x else False)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f426874",
   "metadata": {},
   "source": [
    "#### 10.找出b表名称不在a表中的名称"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "7efa3999",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['宇智波带土', '四代风影', '桃地再不斩'], dtype=object)"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name = pd.merge(b,a,on='名称',how='left') \n",
    "name[name['血型'].isna()].名称.values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b398ecf",
   "metadata": {},
   "source": [
    "# 拓展 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b5af9e",
   "metadata": {},
   "source": [
    "## 1.lambda 函数 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "72ce7c89",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100\n"
     ]
    }
   ],
   "source": [
    "# 匿名函数 \n",
    "# 参数 \n",
    "def power(x):\n",
    "#     返回值\n",
    "    return x**2 \n",
    "resa = power(10)\n",
    "print(resa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "29666ca6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'function'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f1 = lambda x : x**2\n",
    "print(type(f1))\n",
    "f1(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "536745d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'function'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 结构\n",
    "## lambda 参数 ： 返回值（参数操作） \n",
    "\n",
    "def fun_sum(x,y):\n",
    "    return x**2 + y**3 \n",
    "fun_sum(1,2) \n",
    "\n",
    "f2 = lambda x,y : x**2 + y**3\n",
    "print(type(f2))\n",
    "f2(1,2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8dfa85f",
   "metadata": {},
   "source": [
    "## 2.map函数 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "8febc70f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 4, 9, 16]\n"
     ]
    }
   ],
   "source": [
    "# 对指定的序列做映射 \n",
    "def power(x):\n",
    "#     返回值\n",
    "    return x**2 \n",
    "\n",
    "listb = [1,2,3,4]\n",
    "new_listb = []\n",
    "for i in listb:\n",
    "    new_listb.append(power(i))\n",
    "print(new_listb) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "59d4be80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "4\n",
      "9\n",
      "16\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[1, 4, 9, 16]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# map(函数，序列)\n",
    "new_listc = map(power,[1,2,3,4])\n",
    "new_listc \n",
    "for j in new_listc:\n",
    "    print(j)\n",
    "list(map(power,[1,2,3,4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "cc65600d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 4, 9, 16]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(lambda x:x**2 ,[1,2,3,4]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "012380bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[11, 22, 33, 44]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listh = [1,2,3,4] \n",
    "listg = [10,20,30,40] \n",
    "\n",
    "list(map(lambda x,y:x+y, listh,listg ))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb2fa42e",
   "metadata": {},
   "source": [
    "# 3.filter函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "2e9b92f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 3,\n",
       " 6,\n",
       " 9,\n",
       " 12,\n",
       " 15,\n",
       " 18,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 30,\n",
       " 33,\n",
       " 36,\n",
       " 39,\n",
       " 42,\n",
       " 45,\n",
       " 48,\n",
       " 51,\n",
       " 54,\n",
       " 57,\n",
       " 60,\n",
       " 63,\n",
       " 66,\n",
       " 69,\n",
       " 72,\n",
       " 75,\n",
       " 78,\n",
       " 81,\n",
       " 84,\n",
       " 87,\n",
       " 90,\n",
       " 93,\n",
       " 96,\n",
       " 99]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filter(函数，序列)\n",
    "\n",
    "listx = [i for i in range(100)]\n",
    "listx \n",
    "new_listx = []\n",
    "# 找到三的倍数\n",
    "for j in listx:\n",
    "    if j%3 ==0 :\n",
    "        new_listx.append(j) \n",
    "new_listx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "84cce238",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 3,\n",
       " 6,\n",
       " 9,\n",
       " 12,\n",
       " 15,\n",
       " 18,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 30,\n",
       " 33,\n",
       " 36,\n",
       " 39,\n",
       " 42,\n",
       " 45,\n",
       " 48,\n",
       " 51,\n",
       " 54,\n",
       " 57,\n",
       " 60,\n",
       " 63,\n",
       " 66,\n",
       " 69,\n",
       " 72,\n",
       " 75,\n",
       " 78,\n",
       " 81,\n",
       " 84,\n",
       " 87,\n",
       " 90,\n",
       " 93,\n",
       " 96,\n",
       " 99]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def is_three(n):\n",
    "    return n%3 ==0 \n",
    "list(filter(is_three,listx))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "350808a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 3,\n",
       " 6,\n",
       " 9,\n",
       " 12,\n",
       " 15,\n",
       " 18,\n",
       " 21,\n",
       " 24,\n",
       " 27,\n",
       " 30,\n",
       " 33,\n",
       " 36,\n",
       " 39,\n",
       " 42,\n",
       " 45,\n",
       " 48,\n",
       " 51,\n",
       " 54,\n",
       " 57,\n",
       " 60,\n",
       " 63,\n",
       " 66,\n",
       " 69,\n",
       " 72,\n",
       " 75,\n",
       " 78,\n",
       " 81,\n",
       " 84,\n",
       " 87,\n",
       " 90,\n",
       " 93,\n",
       " 96,\n",
       " 99]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(filter(lambda n: n%3==0 ,listx))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99645566",
   "metadata": {},
   "source": [
    "## 总结1\n",
    "\n",
    "### lambda表达式匿名函数  lambda 参数：返回值 \n",
    "### map  映射  map(函数，序列） 得到的结果元素个数与原序列个数一致\n",
    "### filter 过滤  filter(判断函数，序列） 得到的结果元素个数〈=原序列个数\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "1ca1e469",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a  b  c  d\n",
       "1  3  6  6  6\n",
       "2  4  1  0  7\n",
       "3  8  6  4  2\n",
       "4  5  2  2  3"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(np.random.randint(0,10,(4,4)),index=[1,2,3,4],columns=['a','b','c','d']) \n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "2ef45c9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    3\n",
       "2    7\n",
       "3    6\n",
       "4    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# apply 用于一维数组/二维数组，row/column计算\n",
    "# map 用于一维数组 \n",
    "# df.apply(lambda x: x**2) # 针对于每一个元素\n",
    "df.apply(lambda x : x.max()-x.min() ,axis=0)\n",
    "df.apply(lambda x : x.max()-x.min() ,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "8b77dd09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    36\n",
       "2    49\n",
       "3     4\n",
       "4     9\n",
       "Name: d, dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.d.map(lambda x:x**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "84bc7013",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>64</td>\n",
       "      <td>36</td>\n",
       "      <td>16</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    a   b   c   d\n",
       "1   9  36  36  36\n",
       "2  16   1   0  49\n",
       "3  64  36  16   4\n",
       "4  25   4   4   9"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# applymap 用于二维数组中的每一个元素 \n",
    "df.applymap(lambda x:x**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e60ccbe2",
   "metadata": {},
   "source": [
    "## 总结2\n",
    "\n",
    "### apply 用于一维数组， 二维数组 row/column计算\n",
    "### map 用于一维数组 ， 对一维数组中的每一个元素操作\n",
    "### applymap 用于二维数组中的每一个元素操作 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "8ee67251",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'abc'"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listxyz = ['a','b','c'] \n",
    "''.join(listxyz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "8ef5c3d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"['a', 'b', 'c']\""
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(listxyz)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b65a75f1",
   "metadata": {},
   "source": [
    "## 三目运算符"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "14c7c697",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "小于\n"
     ]
    }
   ],
   "source": [
    "x = 1 \n",
    "y = 2 \n",
    "if x>y :\n",
    "    print('大于') \n",
    "else:\n",
    "    print('小于')  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "f804a6fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'小'"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#    A.    if  判断表达式C   else B \n",
    "res = '大'  if x>y  else '小'\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d2fe3182",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "54159c7c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      187\n",
       "1      189\n",
       "2      198\n",
       "3      152\n",
       "4      158\n",
       "      ... \n",
       "163    133\n",
       "164    157\n",
       "165    196\n",
       "166    190\n",
       "167    158\n",
       "Name: phonenum, Length: 168, dtype: object"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.phonenum.str[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "18b0ff22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      187\n",
       "1      189\n",
       "2      198\n",
       "3      152\n",
       "4      158\n",
       "      ... \n",
       "163    133\n",
       "164    157\n",
       "165    196\n",
       "166    190\n",
       "167    158\n",
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